Created by: 20092136

以下是网络和 slot 类型的配置

def lstm_dnn_net(seq_dim,
                feat_dim,
                class_dim,
                emb_dim=128,
                hid_dim=512,
                lstm_dim=128,
                is_predict=False):
    """ 
    lstm 和 DNN 网络
    """
    bias_attr = ParameterAttribute(initial_std=0., l2_rate=0.0001)
    fc_para_attr = ParameterAttribute(learning_rate=2e-3)
    lstm_para_attr = ParameterAttribute(initial_std=0., learning_rate=2e-3)#, sparse_update=True)
    sparse_up = ParameterAttribute(sparse_update=True)
    layer_attr = ExtraLayerAttribute(drop_rate=0.5)
    para_attr = [lstm_para_attr, fc_para_attr]
    relu = ReluActivation()
    linear = LinearActivation()
 
 
    seq_data = data_layer("seq", seq_dim)
    emb = embedding_layer(input=seq_data, size=emb_dim)
    
    bi_lstm = bidirectional_lstm(input=emb, size=lstm_dim, concat_act=relu)
    #dropout = dropout_layer(input=bi_lstm, dropout_rate=0.5)
    lstm_out = fc_layer(input=bi_lstm, size=lstm_dim, act=TanhActivation(),
            bias_attr=bias_attr)
    
    feat_data = data_layer("feat", feat_dim)
    emb2 = embedding_layer(input=feat_data, size=emb_dim)
    feat_layer_1 = fc_layer(input=emb2, size=hid_dim/4, act=relu,
                   bias_attr=bias_attr)#, param_attr=sparse_up)
    feat_layer_2 = fc_layer(input=feat_layer_1, size=hid_dim/4, act=relu, bias_attr=bias_attr)
    output = fc_layer(name='fc_ly_4', input=[lstm_out, feat_layer_2], size=class_dim,
                      act=SoftmaxActivation(),
                      bias_attr=bias_attr, param_attr=para_attr)
    
    if is_predict:
        outputs(output)
    else:
        outputs(
            classification_cost(input=output, label=data_layer('label', 1), 
                evaluator=[precision_recall_evaluator, classification_error_evaluator]))

def hook(obj, dictionary, **kwargs):
    obj.input_types = [integer_value_sequence(len(dictionary)), integer_value_sequence(6121), integer_value(888)]

训练时报错： F1130 14:12:50.641754 18718 Matrix.cpp:378] Check failed: height_ == a.height_ (256 vs. 1390) F1130 14:12:50.643165 18726 Matrix.cpp:378] Check failed: height_ == a.height_ (256 vs. 1327) F1130 14:12:50.643165 18726 Matrix.cpp:378] Check failed: height_ == a.height_ (256 vs. 1327) F1130 14:12:50.644318 18714 Matrix.cpp:378] Check failed: height_ == a.height_ (256 vs. 1408) F1130 14:12:50.643165 18726 Matrix.cpp:378] Check failed: height_ == a.height_ (256 vs. 1327) F1130 14:12:50.644318 18714 Matrix.cpp:378] Check failed: height_ == a.height_ (256 vs. 1408) F1130 14:12:50.645272 18722 Matrix.cpp:378] Check failed: height_ == a.height_ (256 vs. 1387)

请问可能是什么原因？